Self-organized development of behaviors in spatio-temporal dynamical systems
Abstract
Nonlinear distributed modeling is applied to generate conditions for the emergence of intentional behaviors afforded by the environment. The models are based on a nondeterministic dynamical approach to self-organized formation of categories using chaotic principles. Continuous and discrete models of the spatio-temporal dynamics are shown to exhibit phase transitions manifested in the form of intermittent spatio-temporal structures, which are studied in simulated environments.
Publication Title
Proceedings of the International Joint Conference on Neural Networks
Recommended Citation
Kozma, R., & Bollobas, B. (2002). Self-organized development of behaviors in spatio-temporal dynamical systems. Proceedings of the International Joint Conference on Neural Networks, 3, 2261-2264. Retrieved from https://digitalcommons.memphis.edu/facpubs/5655
